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A numerical model of birch pollen emission and dispersion in the atmosphere. Model evaluation and sensitivity analysis
An evaluation of performance of the System for Integrated modeLling of Atmospheric coMposition (SILAM) in application to birch pollen dispersion is presented. The system is described in a companion paper whereas the current study evaluates the model sensitivity to details of the pollen emission modu...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer-Verlag
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3527737/ https://www.ncbi.nlm.nih.gov/pubmed/22434484 http://dx.doi.org/10.1007/s00484-012-0539-5 |
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author | Siljamo, Pilvi Sofiev, Mikhail Filatova, Elena Grewling, Łukasz Jäger, Siegfried Khoreva, Ekaterina Linkosalo, Tapio Ortega Jimenez, Sara Ranta, Hanna Rantio-Lehtimäki, Auli Svetlov, Anton Veriankaite, Laura Yakovleva, Ekaterina Kukkonen, Jaakko |
author_facet | Siljamo, Pilvi Sofiev, Mikhail Filatova, Elena Grewling, Łukasz Jäger, Siegfried Khoreva, Ekaterina Linkosalo, Tapio Ortega Jimenez, Sara Ranta, Hanna Rantio-Lehtimäki, Auli Svetlov, Anton Veriankaite, Laura Yakovleva, Ekaterina Kukkonen, Jaakko |
author_sort | Siljamo, Pilvi |
collection | PubMed |
description | An evaluation of performance of the System for Integrated modeLling of Atmospheric coMposition (SILAM) in application to birch pollen dispersion is presented. The system is described in a companion paper whereas the current study evaluates the model sensitivity to details of the pollen emission module parameterisation and to the meteorological input data. The most important parameters are highlighted. The reference year considered for the analysis is 2006. It is shown that the model is capable of predicting about two-thirds of allergenic alerts, with the odds ratio exceeding 12 for the best setup. Several other statistics corroborate with these estimations. Low-pollen concentration days are also predicted correctly in more than two-thirds of cases. The model experiences certain difficulties only with intermediate pollen concentrations. It is demonstrated that the most important input parameter is the near-surface temperature, the bias of which can easily jeopardise the results. The model sensitivity to random fluctuations of temperature is much lower. Other parameters important at various stages of pollen development, release, and dispersion are precipitation and ambient humidity, as well as wind direction. |
format | Online Article Text |
id | pubmed-3527737 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Springer-Verlag |
record_format | MEDLINE/PubMed |
spelling | pubmed-35277372012-12-21 A numerical model of birch pollen emission and dispersion in the atmosphere. Model evaluation and sensitivity analysis Siljamo, Pilvi Sofiev, Mikhail Filatova, Elena Grewling, Łukasz Jäger, Siegfried Khoreva, Ekaterina Linkosalo, Tapio Ortega Jimenez, Sara Ranta, Hanna Rantio-Lehtimäki, Auli Svetlov, Anton Veriankaite, Laura Yakovleva, Ekaterina Kukkonen, Jaakko Int J Biometeorol Original Paper An evaluation of performance of the System for Integrated modeLling of Atmospheric coMposition (SILAM) in application to birch pollen dispersion is presented. The system is described in a companion paper whereas the current study evaluates the model sensitivity to details of the pollen emission module parameterisation and to the meteorological input data. The most important parameters are highlighted. The reference year considered for the analysis is 2006. It is shown that the model is capable of predicting about two-thirds of allergenic alerts, with the odds ratio exceeding 12 for the best setup. Several other statistics corroborate with these estimations. Low-pollen concentration days are also predicted correctly in more than two-thirds of cases. The model experiences certain difficulties only with intermediate pollen concentrations. It is demonstrated that the most important input parameter is the near-surface temperature, the bias of which can easily jeopardise the results. The model sensitivity to random fluctuations of temperature is much lower. Other parameters important at various stages of pollen development, release, and dispersion are precipitation and ambient humidity, as well as wind direction. Springer-Verlag 2012-03-22 2013 /pmc/articles/PMC3527737/ /pubmed/22434484 http://dx.doi.org/10.1007/s00484-012-0539-5 Text en © The Author(s) 2012 https://creativecommons.org/licenses/by/4.0/ This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited. |
spellingShingle | Original Paper Siljamo, Pilvi Sofiev, Mikhail Filatova, Elena Grewling, Łukasz Jäger, Siegfried Khoreva, Ekaterina Linkosalo, Tapio Ortega Jimenez, Sara Ranta, Hanna Rantio-Lehtimäki, Auli Svetlov, Anton Veriankaite, Laura Yakovleva, Ekaterina Kukkonen, Jaakko A numerical model of birch pollen emission and dispersion in the atmosphere. Model evaluation and sensitivity analysis |
title | A numerical model of birch pollen emission and dispersion in the atmosphere. Model evaluation and sensitivity analysis |
title_full | A numerical model of birch pollen emission and dispersion in the atmosphere. Model evaluation and sensitivity analysis |
title_fullStr | A numerical model of birch pollen emission and dispersion in the atmosphere. Model evaluation and sensitivity analysis |
title_full_unstemmed | A numerical model of birch pollen emission and dispersion in the atmosphere. Model evaluation and sensitivity analysis |
title_short | A numerical model of birch pollen emission and dispersion in the atmosphere. Model evaluation and sensitivity analysis |
title_sort | numerical model of birch pollen emission and dispersion in the atmosphere. model evaluation and sensitivity analysis |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3527737/ https://www.ncbi.nlm.nih.gov/pubmed/22434484 http://dx.doi.org/10.1007/s00484-012-0539-5 |
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